A Multi-Gears Cellular Automata Model for Traffic Flow Based on Kinetics Theory

DOI

10.2991/amms-17.2017.35How to use a DOI?

Keywords

microscopic traffic flow models; cellular automaton; limited uniform acceleration/deceleration capability; heterogeneity of acceleration

Abstract

Traffic flow modeling based on cellular automata (CA) has gained considerable importance as one effective tool to successfully simulate complex traffic systems and understand their behavior. However, most of the existing CA models assumes a constant acceleration rate for the vehicles, which is an over-simplification and should be avoided. In fact, most conventional vehicles have multiple gears transmissions. Thus, when one vehicle reaches its top gear, its acceleration is only a fraction of that available at lower speeds. In this paper, a simple and reliable CA model oriented to faithfully reproduce the acceleration profile of vehicles is proposed. For this purpose, a multi-regime constant acceleration model is introduced. In this way, the proposed model can have many points of discontinuity when a vehicle is accelerating based on the vehicle velocity and multiple gears. Simulation results indicate that the performance of vehicles accelerating from a stopped position is reproduced more in line with that obtained from real vehicles, when a larger number of gears is considered. Moreover, the resulting model is more in line with acceleration profile of the vehicles in the real world without seriously jeopardizing its computational efficiency.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Héctor Alonso Guzmán
AU  - María Elena Lárraga
AU  - Luis Alvarez-Icaza
AU  - Jerónimo Carvajal
PY  - 2017/11
DA  - 2017/11
TI  - A Multi-Gears Cellular Automata Model for Traffic Flow Based on Kinetics Theory
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
PB  - Atlantis Press
SP  - 153
EP  - 158
SN  - 1951-6851
UR  - https://doi.org/10.2991/amms-17.2017.35
DO  - 10.2991/amms-17.2017.35
ID  - Guzmán2017/11
ER  -